Treatment-effect-dependent (non-ancillary) stopping rules are part of many common GSDs including Pocock [1]}, O'Brien & Fleming [2]}, and Haybittle-Peto designs [3]}, [4]}. If the data follow a normal distribution with known variance (without possibility of early stopping), then these designs are most powerful for their \(\alpha \) -spending functions. Similarly, application of Simes test (see [5]}) and its recently proposed modification for sequential testing (see [6]}) cannot have higher power than group sequential tests from [7]} with the same \(\alpha \) -spending function.
